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gohluke

Dayze MCP

by gohluke

List Clarifications

list_clarifications
Read-only

Retrieve a ranked queue of person-typed mentions and duplicate CRM people while auto-dismissing non-person entities and auto-linking existing contacts.

Instructions

Ranked clarification queue: only person-typed mentions + duplicate CRM people. Non-person junk (places, orgs, media, command fragments) is auto-dismissed. Existing contacts auto-link. ($0.05; API key required)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoOptional: entity_mention | duplicate_people
limitNoMax rows 1–50, default 15
auto_cleanupNoAuto-dismiss non-person / auto-link existing (default true)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
messageNo
truncatedNo
clarificationsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.28.0

TDQS

B3.4/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description clearly discloses auto-dismissal and auto-linking behavior, plus cost and API key requirements. However, these behaviors contradict the readOnlyHint=true annotation: auto-dismissing non-person junk and auto-linking existing contacts imply state modification. This is an annotation contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, covering scope, ranking, filtering, side effects, cost, and authentication in just two sentences. There is no filler or redundant restatement of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list-oriented tool with a full input schema and output schema, the description covers scope, behavior, cost, and prerequisites well. The main gap is the conflict between the described auto-cleanup side effects and the readOnlyHint annotation, which undermines the completeness of the tool's metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already well documented. The description adds context like 'ranked' and reinforces the auto-cleanup behavior, but does not add substantial new meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'List clarifications' as a ranked queue, and narrows scope to 'only person-typed mentions + duplicate CRM people'. It clearly explains what the tool returns, but it does not explicitly name sibling tools like dismiss_clarification or bulk_dismiss_clarifications to distinguish itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The context is clear: this is the ranked clarification queue for person mentions and duplicate people, and the API key requirement is stated. However, it does not explicitly say when to prefer this over sibling tools or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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